datavortexweekly Fees
    Updated 4 days ago
    WITH decoded_logs AS (
    SELECT
    l.tx_hash AS transaction_hash,
    t.block_timestamp
    FROM boba.core.fact_event_logs l
    JOIN boba.core.fact_transactions t ON l.tx_hash = t.tx_hash
    WHERE l.contract_address IN (
    '0xaf3da220bc03bdbf9b0280d6e2813ea0ffe03f69',
    '0x78c6db2b6073e762f89a23eb3da71d2feeb18315',
    '0x4f059f8d45230cd5b37544e87eebba033a5f1b17',
    '0x6398a59ca706c11d02de1ea3d921742771bcd06f',
    '0xce4956c398ba118f4eacabca1b32ae97bd31df2a',
    '0x247442181b8baa03b3c7dc0d8e971bd4686db27c',
    '0x48643395833882729032170078bf7791a0999f8c',
    '0x3b444d1dbf68d1cfc64a8158affb6a24a6bdf038',
    '0x2e014fe08247a080f2ed6d230b2594911f9f9a69',
    '0x0ec9d6d21358221cccfc933530a8026038cedc12'
    )
    AND l.topics[0] = '0xd78ad95fa46c994b6551d0da85fc275fe613ce37657fb8d5e3d130840159d822'
    ),
    daily_prices AS (
    SELECT
    DATE_TRUNC('day', HOUR) AS price_date,
    SYMBOL,
    AVG(PRICE) AS avg_price
    FROM boba.price.ez_prices_hourly
    WHERE SYMBOL = 'ETH'
    GROUP BY DATE_TRUNC('day', HOUR), SYMBOL
    ),
    tx_fees AS (
    SELECT DISTINCT
    d.transaction_hash,
    DATE_TRUNC('week', d.block_timestamp) AS week,
    t.tx_fee,
    (t.tx_fee) * p.avg_price AS tx_fee_usd
    FROM decoded_logs d
    Last run: 4 days ago
    WEEK
    TOTAL_TX_FEE_USD
    AVG_TX_FEE_USD
    TRANSACTION_COUNT
    1
    2022-10-10 00:00:00.00024.491946440.344956992171
    2
    2022-10-17 00:00:00.00058.4366646510.3397480503172
    3
    2022-10-24 00:00:00.000154.1706493620.355231911434
    4
    2022-10-31 00:00:00.000162.1158893530.3973428661408
    5
    2022-11-07 00:00:00.000726.3688417170.57329821761267
    6
    2022-11-14 00:00:00.000150.8775307250.34212592441
    7
    2022-11-21 00:00:00.00091.4509971760.2912452139314
    8
    2022-11-28 00:00:00.00082.5519195030.3411236343242
    9
    2022-12-05 00:00:00.00064.6400221450.3802354244170
    10
    2022-12-12 00:00:00.000100.9089292780.3866242501261
    11
    2022-12-19 00:00:00.00091.0878192910.2777067661328
    12
    2022-12-26 00:00:00.00069.9013057370.2864807612244
    13
    2023-01-02 00:00:00.000198.7777833850.3627331814548
    14
    2023-01-09 00:00:00.000184.0748309250.5113189748360
    15
    2023-01-16 00:00:00.000197.9998916940.5265954566376
    16
    2023-01-23 00:00:00.000214.1032795180.5122088027418
    17
    2023-01-30 00:00:00.000218.2368801620.5914278595369
    18
    2023-02-06 00:00:00.000221.7648056660.6446651328344
    19
    2023-02-13 00:00:00.000200.9168136590.6697227122300
    20
    2023-02-20 00:00:00.000291.7067662070.5857565586498
    ...
    134
    8KB
    5s